With the advent of the age of information, and the many emerging insights of systems and co-evolutionary complexity theoretical models, the investigational methods of science, as they especially pertain to education, healthcare, and general optimal performance outcomes, are poised for dramatic improvements. In medical research especially, these new investigational technologies are giving rise to a myriad of new designs for diagnostic equipment, medical devices, and computer-implemented technologies that enable health care professionals to more effectively identify and propose next-generation treatments for numerous human ailments. In education and training contexts, there are similar emerging refinements in biology-based strategies for developing and conveying learning methods and the skillful delivery of content that can be more readily integrated by the brain for optimal utilization and performance.
Traditionally, computer and information technology have been used by health care professionals in several basic ways: to physically interact with patients, to visualize certain areas of the body which were previously inaccessible, or to perform complex computations crucial to patient diagnosis and treatment. However, in recent years computer and information technology have been used to interact with and treat patients in a different manner. An example of the use of computers in the treatment of human ailments is the use of biofeedback for therapeutic “games.”
Some therapeutic games treat ailments using interactive devices that help patients visualize and control their own previously involuntary biological attributes. Enhancing such visible access to these biological attributes may be relevant to any number ailments suffered by a patient. For example, see U.S. Pat. No. 4,461,301 to Ochs (“Self Adjusting Bio-Feedback Method and Apparatus”), U.S. Pat. No. 5,377,100 to Pope et al. (“Method of Encouraging Attention by Correlating Video Game Difficulty with Attention Level”), U.S. Pat. No. 5,678,571 to Brown (“Method for Treating Medical Conditions Using a Microprocessor-Based Video Game”), each of which are hereby incorporated by reference herein in their entirety. As such, increasing access to parameters that function to control these attributes may enable new treatment of ailments. Therapeutic games often incorporate visualization of these biological attributes into any number of game formats. These therapeutic biofeedback games have been employed in the treatment of ailments such as attention deficit hyperactivity disorder (ADHD), addiction, learning disabilities, schizophrenia, and various other conditions.
Traditional approaches to science, engineering, learning, medicine, and even biofeedback treatment and training often begin with an investigation into the component parts of a system. Once the component parts of a system have been identified, deconstructed, and analyzed, it is generally assumed that the complete function of the system, and thus, any malfunctions thereof, may be derived from the sum of these parts. This “reductionistic” method of science may prove useful in discerning some basic qualities of a system and solving basic problems therein. However, reductionistic methods and their attendant stimulus-response models are based on a limiting understanding of the core causalities that inform complex and dynamic living systems. There exist qualities that may be discerned and implemented only when the “system-as-a-whole” (i.e., holistic) and the controllers of its synergistic self-organizing regulatory networks are accessed, visualized, and better understood as a functional “context.”
The complexity of living relationships responsible for controlling the health of a human being, for instance, may be hidden deep within the expressive patterns of genetic and epigenetic regulatory networks. Developing methods that provide a whole-systems approach and access to these networks and their environmental contexts may be available only through a skillful convergence of real-time-living and virtual combinatorial interactions.
Controller strategies evolved by nature have enabled life on earth to survive for eons, adapting to changes by exhibiting phase transitions resulting in autonomous self-organizing, collective, and co-operative capacities. Solutions to complex medical and educational puzzles, as an example, may lie in the living repository of these most co-evolutionarily conserved genetic co-expression contexts, bio-pathways and the regulatory triggers that promote or silence them. In light of such realizations, there is a need and opportunity to include methods beyond those of reductionistic science, which are exemplified by traditional stimulus-response models of causality.
The present invention co-evolutionarily confirms its optimization measures by the integration of the above-mentioned deeply conserved measurable artifacts of evolution. The invention also provides access to the “states” that inform phase-state transitions operating in dynamic systems such as, for example, the brain.